Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …

Sky-image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty in solar power generation. However, one of …

People can infer the weather from clouds. Various weather phenomena are linked
inextricably to clouds, which can be observed by meteorological satellites. Thus, cloud …

In recent years, convolutional neural networks (CNNs) have achieved competitive
performance in the field of ground-based cloud image (GCI) classification. Proposed CNN …

Cloud classification is a great challenge in meteorological research. The different types of
clouds, currently known and present in our skies, can produce radioactive effects that impact …

Most ground-based remote sensing cloud classification methods focus on learning
representation features for cloud images while ignoring the correlations among cloud …

Cloud observation serves as the fundamental bedrock for acquiring comprehensive cloud-
related information. The categorization of distinct ground-based clouds holds profound …

摘要深度学习的自动学习特征和精确的预测能力使其在地基云分类上获得成功,
更复杂更优良的深度学习网络在地基云分类领域得到研究和应用. 近两年来一些大规模地基云 …

In recent years, convolutional neural networks have been in the leading position for ground-
based cloud image classification tasks. However, this approach introduces too much …

Changes in clouds can affect the outpower of photovoltaics (PVs). Ground-based cloud
images classification is an important prerequisite for PV power prediction. Due to the intra …